Luca Ambrogioni
16 papers · 2017–2025 · 5 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (25) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge · Bronze
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Topic Evolution
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Keyword Champion
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Unstoppable · Bronze
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Keyword Collector
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Century Club · Bronze
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Research topics
Machine Learning
(12)
Deep Learning
(11)
Models
(10)
Optimization & Theory · Machine Learning
(9)
Artificial Intelligence
(7)
Bayesian & Probabilistic · Artificial Intelligence
(7)
Core Methods
(4)
Bayesian & Probabilistic · Machine Learning
(3)
Interdisciplinary
(2)
Optimization & Theory · Deep Learning
(2)
Science
(2)
Computer Vision
(1)
Data Science & Analytics
(1)
Architectures
(1)
Core AI
(1)
Keywords
variational inference
(5)
normalizing flow
(3)
diffusion model
(2)
gaussian process regression
(2)
bayesian inference
(2)
generative model
(2)
variational autoencoder
(2)
causal inference
(2)
probabilistic programming
(2)
deep learning
(1)
flow matching
(1)
likelihood-free inference
(1)
probabilistic modeling
(1)
signal processing
(1)
stochastic gradient descent
(1)
optimal transport
(1)
brain connectivity
(1)
image generation
(1)
gaussian process
(1)
maximum likelihood
(1)
Papers
Dynamic Negative Guidance of Diffusion Models
ICLR 2025
Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion
ICLR 2025
VCT: Training Consistency Models with Variational Noise Coupling
ICML 2025
Stationarity without mean reversion in improper Gaussian processes
ICML 2024
Deterministic training of generative autoencoders using invertible layers
ICLR 2023
Spontaneous symmetry breaking in generative diffusion models
NeurIPS 2023
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling
ICLR 2022
Automatic structured variational inference
AISTATS 2021
Automatic variational inference with cascading flows
ICML 2021
GAIT-prop: A biologically plausible learning rule derived from backpropagation of error
NeurIPS 2020
The Indian Chefs Process
UAI 2020
Forward Amortized Inference for Likelihood-Free Variational Marginalization
AISTATS 2019
SpikeCaKe: Semi-Analytic Nonparametric Bayesian Inference for Spike-Spike Neuronal Connectivity
AISTATS 2019
Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis
AISTATS 2018
Wasserstein Variational Inference
NeurIPS 2018
GP CaKe: Effective brain connectivity with causal kernels
NeurIPS 2017